Using a High-Speed Mini-PC to Control an Autonomous Underwater Vehicle

Ali. Jebelli^1, , Mustapha C.E. Yagoub¹ and Balbir S. Dhillon²

¹School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada

²Department of Mechanical Engineering, University of Ottawa, Ottawa, Canada

Cite this paper:
Ali. Jebelli, Mustapha C.E. Yagoub and Balbir S. Dhillon. Using a High-Speed Mini-PC to Control an Autonomous Underwater Vehicle. American Journal of Mechanical Engineering. 2019; 7(3):116-128. doi: 10.12691/ajme-7-3-2

Abstract

In this paper, the authors present the design of a mini-PC board to fast processing of an AUV (Autonomous Underwater Vehicle) with two 360° rotational thrusters. This rotation capability in the thrusters, along with an embedded mass shifter, allows for long-time immersive motor maneuvers for this AUV. Also, the conditions for moving the device at the water surface and depth are provided by changing the angle of the thrusters and moving the mass shifter along with the motor speed change. All the commands related to the motor angles, proper position of the thrusters, mass shifter, and speed, are sent to an Engine board via a high-speed Mini PC. The high-speed Mini PC sends decisions to the Engine board after receiving and processing all sensors data as well as data from embedded cameras. This integrated system provides the ability to move safely based on accurate analysis of the environment by sensors and images received by cameras from the surroundings, with minimal energy consumption for the underwater AUV. The results of various tests demonstrated the high performance of this AUV.

Keywords:
autonomous underwater vehicle PTFE Mini-PC

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References:

[1]	Jebelli, A., “Design of an Autonomous Underwater Vehicle with Vision Capabilities,” Ph.D Thesis, University of Ottawa, 2016.
[2]	Jebelli, A., “Development of Sensors and Microcontrollers for Underwater Robots,” Master’s Thesis, University of Ottawa, 2014.
[3]	Jebelli, A., Yagoub, M.C.E, Dhillon, B.S., “Design and control of a self-balancing autonomous underwater vehicle with vision capabilities,” Journal of Marine Science: Research & Development, Vol. 8, No. 1, pp. 1-7, 2018.
[4]	Jebelli, A., Yagoub, M.C.E, Dhillon, B.S., “Modeling of an autonomous underwater robot with rotating thrusters,” Advances in Robotics and Automation, Vol. 6, No. 1, pp. 1-10, 2017.
[5]	Zhao, Y., Wang, L. and Peng, S., “A Real-Time Collision Avoidance Learning System for Unmanned Surface Vessels,” Neurocomputing, 182, pp. 255-266, 2016.
[6]	i200, 4th Gen. Intel® CoreTM i3/i5/i7 Processor Intel® HD Graphics 4400, Intel, 2015.
[7]	MPU-9250 Product Specification, Document Number: PS-MPU-9250A-01, InvenSense Inc, 2014.
[8]	Three-axis Compass with Algorithms HMC6343, Honeywell’s Magnetic Sensors, 2014.
[9]	126MS5803-14BA Miniature 14 bar Module, Measurement Specialties Inc., 2012.
[10]	http://www.atmel.com/images/atmel-2490-8-bit-avr-microcontroller-atmega64- l_datasheet.pdf, [Last access May 23, 2018].
[11]	FSK/ASK Transceiver IC, Analog Devices, Inc., 2012.
[12]	KeyStone Architecture Universal Asynchronous Receiver/Transmitter, Texas Instruments, 2010.
[13]	http://www.dorji.com/docs/data/DRF7020D13.pdf, [Last access May 25, 2018].
[14]	BTN7971B High Current PN Half Bridge NovalithIC, Infineon Techn., 2008.
[15]	http://www.buehlermotor.de/C12572D40025EAF8/vwContentByKey/W274AHF53 91 WEBRDE/$File/DC- Motor_51x73_1.13.044.0XX.pdf, [Last access May 27, 2018].
[16]	http://www.motionusa.com.s3-website-us-east-1.amazonaws.com/moons/Hybrid _Stepper_Motors_16HS_Series.pdf, [Last access May 18, 2018].